def initialize(context):
attach_pipeline(make_pipeline(), 'my_pipeline')
context.sector_wise_exposure = dict()
context.sector_stocks = {}
context.turnover_count = 0
if context.live_trading is False:
schedule_function(stop_loss, date_rule=date_rules.month_start())
schedule_function(rebalance, date_rule=date_rules.month_start())
def before_trading_start(context, data):
context.pipeline_data = pipeline_output('my_pipeline')
if context.live_trading is True:
try:
with open('sector_list.pickle', 'rb') as handle:
context.sector_stocks = pickle.load(handle)
except:
context.sector_stocks = {}
schedule_function(stop_loss, date_rule=date_rules.month_start())
schedule_function(rebalance, date_rule=date_rules.month_start())
context.logic_run_done = False
def get_date_rules(freq):
if freq == "day":
start_rule = date_rules.every_day()
end_rule = date_rules.every_day()
elif freq == "week":
start_rule = date_rules.week_start()
end_rule = date_rules.week_end()
elif freq == "month":
start_rule = date_rules.month_start()
end_rule = date_rules.month_end()
else:
start_rule = date_rules.every_day()
end_rule = date_rules.every_day()
date_rule = {"start": start_rule, "end": end_rule}
time_rule = {
"start": time_rules.market_open(),
"end": time_rules.market_close()
}
return date_rule, time_rule
def initialize_testing_algo(self, context):
set_commission(PerShare())
set_slippage(VolumeShareSlippage())
if self.syms is None:
self.syms = self.__validate_symbols__(self.ticker_syms)
self.portfolio_memory = PortfolioMemory(len(self.syms),
self.config.n_history)
schedule_function(self.testing_rebalance,
date_rule=date_rules.month_start(),
time_rule=time_rules.market_open(minutes=1))
def initialize(context):
attach_pipeline(make_pipeline(), 'my_pipeline')
# context.broker = BacktestBroker()
context.stop_loss_list = pd.Series()
context.sector_wise_exposure = dict()
context.sector_stocks = {}
context.turnover_count = 0
if context.live_trading is False:
schedule_function(rebalance, date_rule=date_rules.month_start())
def initialize(context):
# attach_pipeline(make_pipeline(), 'my_pipeline')
context.turnover_count = 0
# etf stock
context.shorting_on = True
context.longStock = symbol('IVV')
context.shortStock = symbol('SH')
if context.live_trading is False:
schedule_function(monthly_rebalance,
date_rule=date_rules.month_start())
def initialize(context):
c = context
# Some Risk-On universes
core_etf = symbols('QQQ', 'XLP', 'TLT', 'IEF')
tact_etf = symbols('XLV', 'XLY', 'TLT', 'GLD')
VAAG12 = symbols('SPY', 'IWM', 'QQQ', 'VGK', 'EWJ', 'VWO', 'VNQ', 'GSG',
'GLD', 'TLT', 'LQD', 'HYG')
VAAG4 = symbols('SPY', 'VEA', 'VWO', 'BND')
c.RISK = VAAG4 # Which Riskasset universe to use?
alletf = symbols('QQQ', 'XLP', 'TLT', 'IEF', 'SPY', 'IWM', 'QQQ', 'VGK',
'EWJ', 'VWO', 'VNQ', 'GSG', 'GLD', 'TLT', 'LQD', 'HYG',
'XLV', 'XLY', 'GLD', 'VEA') # 'TLO' repleced by 'TLT'
# Some Risk Off (Cash) universes
c.CASH = symbols('SHY', 'IEF', 'LQD')
schedule_function(define_weights, date_rules.month_end(Month_Offset),
time_rules.market_open(minutes=64))
log.info('define_weights for last trading day of the month')
schedule_function(trade_sell, date_rules.month_end(Month_Offset),
time_rules.market_open(minutes=65))
log.info('trade_sell for last trading day of the month')
if TplusX > 0:
schedule_function(
trade_buy, date_rules.month_start(max(0,
TplusX - 1 - Month_Offset)),
time_rules.market_open(minutes=66))
log.info('trade_buy for month day ' +
str(max(0, TplusX - Month_Offset)))
else:
schedule_function(trade_buy, date_rules.month_end(Month_Offset),
time_rules.market_open(minutes=66))
log.info('trade_buy last trading day of the month')
stocks = core_etf + tact_etf
context.sell = {}
context.buy = {}
for stock in stocks:
context.sell[stock] = 0
context.buy[stock] = 0
context.difference_perc = 0.02
context.stops = {}
context.stoploss = 0.30
context.stoppedout = []
def before_trading_start(context, data):
# context.pipeline_data = pipeline_output('my_pipeline')
if context.live_trading is True:
schedule_function(monthly_rebalance,
date_rule=date_rules.month_start())
context.logic_run_done = False